1. Moving objects in a geo-DBMS
Structuring, indexing, querying and visualizing moving objects in a spatiotemporal DBMS
Heraklion, Agile 2004
Marco Baars*, Peter van Oosterom, Edward Verbree, Ben Gorte
November 27, 2018
OTB Research Institute for Housing, Urban and Mobility Studies
Section GIS Technology

2. Content Introduction of the subject
Generic model for moving object DMBS
Case I: static modeling
Case II: dynamic modeling
Conclusions and recommendations
November 27, 2018

3. Introduction Spatiotemporal DBMSs become popular
Traffic jams, cadastral issues
Database is remained to stay constant
New challenge for moving objects in database
Databases useful for
Large datasets
Easy querying
Consistency, security, redundancy, interoperability
November 27, 2018

4. Introduction – Main question
What is the potential and performance of the Oracle Spatial geo-DBMS to structure, index, query and visualize spatiotemporal point clouds of moving objects?
November 27, 2018

5. Introduction Vazirgiannis/Wolfson Map Moving object Trajectory
Characteristic:
Developed for specific application
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6. Generic model
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7. Generic model Base table: CREATE TABLE mov_obj
(id, t, geometry) –-prim.key = id,t
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8. Generic model Base table with (materialized) views
CREATE VIEW move_obj_succ AS
SELECT t1.*, t2.t as next_t
FROM mov_obj t1, mov_obj t2
WHERE t1.id=t2.id and t2.t=(select min(t) from move_obj where t>t1.t);
Flexible, consistent and fast
November 27, 2018

9. Case I: Static modeling
Data (id,x,y,t) collected in advance
One “base table” with views in Oracle 9i Spatial
Querying based on operators and functions
Operator: sdo_relate
in where-clause
Index necessary
Function: sdo_geom.relate
Visualization (animation)
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10. Case I: Static modeling
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11. Case II: Dynamic modeling
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12. Case II: Dynamic modeling
Real-time simulation
(growing table)
2D and 3D
indexing tests
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13. Case II: Dynamic modeling
2D Query “SDO_RELATE”
3D Query “SDO_FILTER”
x1,y1,t1
x0,y0,t0
November 27, 2018

14. Conclusions
Generic model is flexible, fast and consistent for static and dynamic point data
Choice for “base table” has to be made and depends on:
2D or 3D queries
2D or 3D index
Update time for index depends on covered area and number of objects in growing table
November 27, 2018

15. Future Research Prove Generic Model for 4D data (x,y,z,t)
Test the ArcIMS Tracking Server
Implementing more efficient R-tree
Test model for polylines, polygons or polyhedrons
November 27, 2018